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Generative optimization of bistable plates with deep learning
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作者 Hong Li Qingfeng Wang 《Theoretical & Applied Mechanics Letters》 CAS CSCD 2024年第1期35-38,共4页
Bistate plates have found extensive applications in the domains of smart structures and energy harvesting devices.Most bistable curved plates are characterized by a constant thickness profile.Regrettably,due to the in... Bistate plates have found extensive applications in the domains of smart structures and energy harvesting devices.Most bistable curved plates are characterized by a constant thickness profile.Regrettably,due to the inherent complexity of this problem,relatively little attention has been devoted to this area.In this study,we demonstrate how deep learning can facilitate the discovery of novel plate profiles that cater to multiple objectives,including maximizing stiffness,forward snapping force,and backward snapping force.Our proposed approach is distinguished by its efficiency in terms of low computational energy consumption and high effectiveness.It holds promise for future applications in the design and optimization of multistable structures with diverse objectives,addressing the requirements of various fields. 展开更多
关键词 bistable plate Nonlinear MICROSTRUCTURE Simulation Machine learning
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